| Best model | name | model_type | metric_type | metric_value | train_time |
|---|---|---|---|---|---|
| 1_DecisionTree | Decision Tree | logloss | 0.295041 | 5.33 | |
| 2_DecisionTree | Decision Tree | logloss | 0.313541 | 5.19 | |
| 3_DecisionTree | Decision Tree | logloss | 0.313541 | 5.32 | |
| 4_Linear | Linear | logloss | 0.18766 | 6.13 | |
| 5_Default_LightGBM | LightGBM | logloss | 0.125001 | 11.22 | |
| 6_Default_Xgboost | Xgboost | logloss | 0.132326 | 9.43 | |
| 7_Default_CatBoost | CatBoost | logloss | 0.114824 | 10.61 | |
| 8_Default_NeuralNetwork | Neural Network | logloss | 0.187465 | 8.11 | |
| 9_Default_RandomForest | Random Forest | logloss | 0.228603 | 11.64 | |
| 10_Default_ExtraTrees | Extra Trees | logloss | 0.193979 | 10.97 | |
| 11_Default_NearestNeighbors | Nearest Neighbors | logloss | 0.447072 | 7.98 | |
| 21_LightGBM | LightGBM | logloss | 0.142061 | 11.57 | |
| 12_Xgboost | Xgboost | logloss | 0.163252 | 10.06 | |
| 30_CatBoost | CatBoost | logloss | 0.111399 | 35.02 | |
| 39_RandomForest | Random Forest | logloss | 0.204734 | 13.2 | |
| 48_ExtraTrees | Extra Trees | logloss | 0.184721 | 12.91 | |
| 57_NeuralNetwork | Neural Network | logloss | 0.254356 | 9.92 | |
| 66_NearestNeighbors | Nearest Neighbors | logloss | 0.488837 | 9.7 | |
| 22_LightGBM | LightGBM | logloss | 0.119728 | 12.26 | |
| 13_Xgboost | Xgboost | logloss | 0.132156 | 14.02 | |
| 31_CatBoost | CatBoost | logloss | 0.116745 | 22.66 | |
| 40_RandomForest | Random Forest | logloss | 0.213752 | 15.61 | |
| 49_ExtraTrees | Extra Trees | logloss | 0.179832 | 14.59 | |
| 58_NeuralNetwork | Neural Network | logloss | 0.164998 | 12.16 | |
| 67_NearestNeighbors | Nearest Neighbors | logloss | 0.437341 | 11.41 | |
| 23_LightGBM | LightGBM | logloss | 0.131008 | 15.33 | |
| 14_Xgboost | Xgboost | logloss | 0.299213 | 12.68 | |
| 32_CatBoost | CatBoost | logloss | 0.109369 | 19.88 | |
| 41_RandomForest | Random Forest | logloss | 0.253847 | 16.45 | |
| 50_ExtraTrees | Extra Trees | logloss | 0.254352 | 16.07 | |
| 59_NeuralNetwork | Neural Network | logloss | 0.147187 | 13.83 | |
| 68_NearestNeighbors | Nearest Neighbors | logloss | 0.437341 | 12.07 | |
| 24_LightGBM | LightGBM | logloss | 0.126845 | 15.89 | |
| 15_Xgboost | Xgboost | logloss | 0.693099 | 12.81 | |
| 33_CatBoost | CatBoost | logloss | 0.11248 | 20.05 | |
| 42_RandomForest | Random Forest | logloss | 0.277495 | 19.01 | |
| 51_ExtraTrees | Extra Trees | logloss | 0.216421 | 16.81 | |
| 60_NeuralNetwork | Neural Network | logloss | 0.248498 | 14.5 | |
| 69_NearestNeighbors | Nearest Neighbors | logloss | 0.488837 | 13.75 | |
| 25_LightGBM | LightGBM | logloss | 0.122106 | 15.44 | |
| 16_Xgboost | Xgboost | logloss | 0.693123 | 14 | |
| 34_CatBoost | CatBoost | logloss | 0.101761 | 19.06 | |
| 43_RandomForest | Random Forest | logloss | 0.27513 | 18.41 | |
| 52_ExtraTrees | Extra Trees | logloss | 0.240711 | 19.21 | |
| 61_NeuralNetwork | Neural Network | logloss | 0.228268 | 15.97 | |
| 70_NearestNeighbors | Nearest Neighbors | logloss | 0.507229 | 15.64 | |
| 26_LightGBM | LightGBM | logloss | 0.127732 | 19.15 | |
| 17_Xgboost | Xgboost | logloss | 0.43164 | 15.93 | |
| 35_CatBoost | CatBoost | logloss | 0.115992 | 18.36 | |
| 44_RandomForest | Random Forest | logloss | 0.261804 | 18.8 | |
| 53_ExtraTrees | Extra Trees | logloss | 0.299218 | 22.85 | |
| 62_NeuralNetwork | Neural Network | logloss | 0.176633 | 17.77 | |
| 71_NearestNeighbors | Nearest Neighbors | logloss | 0.488837 | 16.6 | |
| 27_LightGBM | LightGBM | logloss | 0.13886 | 19.74 | |
| 18_Xgboost | Xgboost | logloss | 0.1746 | 19.75 | |
| 36_CatBoost | CatBoost | logloss | 0.114289 | 51.53 | |
| 45_RandomForest | Random Forest | logloss | 0.235061 | 22.4 | |
| 54_ExtraTrees | Extra Trees | logloss | 0.220836 | 21.08 | |
| 63_NeuralNetwork | Neural Network | logloss | 0.21853 | 18.39 | |
| 72_NearestNeighbors | Nearest Neighbors | logloss | 0.489052 | 18.02 | |
| 28_LightGBM | LightGBM | logloss | 0.116853 | 20.88 | |
| 19_Xgboost | Xgboost | logloss | 0.691893 | 18.25 | |
| 37_CatBoost | CatBoost | logloss | 0.11095 | 27.31 | |
| 46_RandomForest | Random Forest | logloss | 0.195568 | 23.11 | |
| 55_ExtraTrees | Extra Trees | logloss | 0.175504 | 22.43 | |
| 64_NeuralNetwork | Neural Network | logloss | 0.188742 | 20.6 | |
| 29_LightGBM | LightGBM | logloss | 0.141791 | 22.05 | |
| 20_Xgboost | Xgboost | logloss | 0.129838 | 23.47 | |
| 38_CatBoost | CatBoost | logloss | 0.109186 | 43 | |
| 47_RandomForest | Random Forest | logloss | 0.276271 | 23.77 | |
| 34_CatBoost_GoldenFeatures | CatBoost | logloss | 0.105791 | 33.22 | |
| 38_CatBoost_GoldenFeatures | CatBoost | logloss | 0.10771 | 37.51 | |
| 32_CatBoost_GoldenFeatures | CatBoost | logloss | 0.111014 | 28.44 | |
| 34_CatBoost_KMeansFeatures | CatBoost | logloss | 0.100147 | 31.69 | |
| 38_CatBoost_KMeansFeatures | CatBoost | logloss | 0.096346 | 51.72 | |
| 73_CatBoost | CatBoost | logloss | 0.0992113 | 46.54 | |
| 74_CatBoost | CatBoost | logloss | 0.0989191 | 76.72 | |
| 75_CatBoost | CatBoost | logloss | 0.099829 | 32.25 | |
| 76_CatBoost | CatBoost | logloss | 0.098331 | 39.46 | |
| 77_CatBoost | CatBoost | logloss | 0.105146 | 24.75 | |
| 78_CatBoost | CatBoost | logloss | 0.11485 | 31.32 | |
| 79_LightGBM | LightGBM | logloss | 0.123575 | 23.95 | |
| 80_LightGBM | LightGBM | logloss | 0.119156 | 26.91 | |
| 81_LightGBM | LightGBM | logloss | 0.117737 | 25.96 | |
| 82_LightGBM | LightGBM | logloss | 0.119728 | 25.24 | |
| 83_CatBoost | CatBoost | logloss | 0.0934722 | 41.33 | |
| 84_CatBoost | CatBoost | logloss | 0.103991 | 51.4 | |
| 85_CatBoost | CatBoost | logloss | 0.10591 | 33.37 | |
| 86_CatBoost | CatBoost | logloss | 0.0964026 | 57.86 | |
| 83_CatBoost_BoostOnErrors | CatBoost | logloss | 0.0933352 | 44.61 | |
| the best | Ensemble | Ensemble | logloss | 0.0914001 | 29.38 |
logloss
10.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.193979 | nan |
| auc | 0.974161 | nan |
| f1 | 0.92779 | 0.512511 |
| accuracy | 0.927948 | 0.512511 |
| precision | 1 | 0.774203 |
| recall | 1 | 0.0166806 |
| mcc | 0.856244 | 0.603755 |
| score | threshold | |
|---|---|---|
| logloss | 0.193979 | nan |
| auc | 0.974161 | nan |
| f1 | 0.92779 | 0.512511 |
| accuracy | 0.927948 | 0.512511 |
| precision | 0.929825 | 0.512511 |
| recall | 0.925764 | 0.512511 |
| mcc | 0.855903 | 0.512511 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 213 | 16 |
| Labeled as 1 | 17 | 212 |
logloss
7.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.447072 | nan |
| auc | 0.971263 | nan |
| f1 | 0.950749 | 0 |
| accuracy | 0.949782 | 0 |
| precision | 0.981928 | 0.8 |
| recall | 0.969432 | 0 |
| mcc | 0.900259 | 0 |
| score | threshold | |
|---|---|---|
| logloss | 0.447072 | nan |
| auc | 0.971263 | nan |
| f1 | 0.950749 | 0 |
| accuracy | 0.949782 | 0 |
| precision | 0.932773 | 0 |
| recall | 0.969432 | 0 |
| mcc | 0.900259 | 0 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 213 | 16 |
| Labeled as 1 | 7 | 222 |
logloss
9.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.163252 | nan |
| auc | 0.981637 | nan |
| f1 | 0.958057 | 0.40206 |
| accuracy | 0.958515 | 0.40206 |
| precision | 1 | 0.945241 |
| recall | 1 | 0.000494429 |
| mcc | 0.917249 | 0.40206 |
| score | threshold | |
|---|---|---|
| logloss | 0.163252 | nan |
| auc | 0.981637 | nan |
| f1 | 0.958057 | 0.40206 |
| accuracy | 0.958515 | 0.40206 |
| precision | 0.96875 | 0.40206 |
| recall | 0.947598 | 0.40206 |
| mcc | 0.917249 | 0.40206 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 12 | 217 |
logloss
13.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.132156 | nan |
| auc | 0.987195 | nan |
| f1 | 0.961039 | 0.194584 |
| accuracy | 0.960699 | 0.194584 |
| precision | 1 | 0.954132 |
| recall | 1 | 4.70754e-07 |
| mcc | 0.921538 | 0.194584 |
| score | threshold | |
|---|---|---|
| logloss | 0.132156 | nan |
| auc | 0.987195 | nan |
| f1 | 0.961039 | 0.194584 |
| accuracy | 0.960699 | 0.194584 |
| precision | 0.95279 | 0.194584 |
| recall | 0.969432 | 0.194584 |
| mcc | 0.921538 | 0.194584 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 7 | 222 |
logloss
12.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.299213 | nan |
| auc | 0.960813 | nan |
| f1 | 0.917749 | 0.406873 |
| accuracy | 0.917031 | 0.406873 |
| precision | 1 | 0.85484 |
| recall | 1 | 0.0303831 |
| mcc | 0.834571 | 0.489605 |
| score | threshold | |
|---|---|---|
| logloss | 0.299213 | nan |
| auc | 0.960813 | nan |
| f1 | 0.917749 | 0.406873 |
| accuracy | 0.917031 | 0.406873 |
| precision | 0.909871 | 0.406873 |
| recall | 0.925764 | 0.406873 |
| mcc | 0.834188 | 0.406873 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 208 | 21 |
| Labeled as 1 | 17 | 212 |
logloss
12.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.693099 | nan |
| auc | 0.503938 | nan |
| f1 | 0.666667 | 0.441526 |
| accuracy | 0.502183 | 0.490584 |
| precision | 0.511111 | 0.500094 |
| recall | 1 | 0.441526 |
| mcc | 0.00733531 | 0.490584 |
| score | threshold | |
|---|---|---|
| logloss | 0.693099 | nan |
| auc | 0.503938 | nan |
| f1 | 0.64486 | 0.490584 |
| accuracy | 0.502183 | 0.490584 |
| precision | 0.501211 | 0.490584 |
| recall | 0.90393 | 0.490584 |
| mcc | 0.00733531 | 0.490584 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 23 | 206 |
| Labeled as 1 | 22 | 207 |
logloss
13.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.693123 | nan |
| auc | 0.503938 | nan |
| f1 | 0.666667 | 0.448216 |
| accuracy | 0.502183 | 0.498018 |
| precision | 0.511111 | 0.500169 |
| recall | 1 | 0.448216 |
| mcc | 0.00733531 | 0.498018 |
| score | threshold | |
|---|---|---|
| logloss | 0.693123 | nan |
| auc | 0.503938 | nan |
| f1 | 0.64486 | 0.498018 |
| accuracy | 0.502183 | 0.498018 |
| precision | 0.501211 | 0.498018 |
| recall | 0.90393 | 0.498018 |
| mcc | 0.00733531 | 0.498018 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 23 | 206 |
| Labeled as 1 | 22 | 207 |
logloss
15.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.43164 | nan |
| auc | 0.89983 | nan |
| f1 | 0.836576 | 0.384851 |
| accuracy | 0.820961 | 0.51912 |
| precision | 0.929577 | 0.791228 |
| recall | 1 | 0.0919202 |
| mcc | 0.653014 | 0.384851 |
| score | threshold | |
|---|---|---|
| logloss | 0.43164 | nan |
| auc | 0.89983 | nan |
| f1 | 0.824034 | 0.51912 |
| accuracy | 0.820961 | 0.51912 |
| precision | 0.810127 | 0.51912 |
| recall | 0.838428 | 0.51912 |
| mcc | 0.642313 | 0.51912 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 184 | 45 |
| Labeled as 1 | 37 | 192 |
logloss
19.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.1746 | nan |
| auc | 0.980979 | nan |
| f1 | 0.946429 | 0.510883 |
| accuracy | 0.947598 | 0.510883 |
| precision | 1 | 0.888737 |
| recall | 1 | 0.00443593 |
| mcc | 0.89739 | 0.563837 |
| score | threshold | |
|---|---|---|
| logloss | 0.1746 | nan |
| auc | 0.980979 | nan |
| f1 | 0.946429 | 0.510883 |
| accuracy | 0.947598 | 0.510883 |
| precision | 0.968037 | 0.510883 |
| recall | 0.925764 | 0.510883 |
| mcc | 0.896051 | 0.510883 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 17 | 212 |
logloss
17.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.691893 | nan |
| auc | 0.539053 | nan |
| f1 | 0.666667 | 0.416477 |
| accuracy | 0.524017 | 0.492134 |
| precision | 0.657143 | 0.501211 |
| recall | 1 | 0.416477 |
| mcc | 0.0904042 | 0.501211 |
| score | threshold | |
|---|---|---|
| logloss | 0.691893 | nan |
| auc | 0.539053 | nan |
| f1 | 0.653968 | 0.492134 |
| accuracy | 0.524017 | 0.492134 |
| precision | 0.513716 | 0.492134 |
| recall | 0.899563 | 0.492134 |
| mcc | 0.0727584 | 0.492134 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 34 | 195 |
| Labeled as 1 | 23 | 206 |
logloss
4.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.295041 | nan |
| auc | 0.930369 | nan |
| f1 | 0.878543 | 0.381818 |
| accuracy | 0.877729 | 0.594595 |
| precision | 1 | 0.931818 |
| recall | 1 | 0.028481 |
| mcc | 0.755487 | 0.594595 |
| score | threshold | |
|---|---|---|
| logloss | 0.295041 | nan |
| auc | 0.930369 | nan |
| f1 | 0.877193 | 0.594595 |
| accuracy | 0.877729 | 0.594595 |
| precision | 0.881057 | 0.594595 |
| recall | 0.873362 | 0.594595 |
| mcc | 0.755487 | 0.594595 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 202 | 27 |
| Labeled as 1 | 29 | 200 |
logloss
22.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.129838 | nan |
| auc | 0.986861 | nan |
| f1 | 0.960699 | 0.330348 |
| accuracy | 0.960699 | 0.330348 |
| precision | 1 | 0.974077 |
| recall | 1 | 3.12422e-07 |
| mcc | 0.921538 | 0.464209 |
| score | threshold | |
|---|---|---|
| logloss | 0.129838 | nan |
| auc | 0.986861 | nan |
| f1 | 0.960699 | 0.330348 |
| accuracy | 0.960699 | 0.330348 |
| precision | 0.960699 | 0.330348 |
| recall | 0.960699 | 0.330348 |
| mcc | 0.921397 | 0.330348 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
logloss
10.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.142061 | nan |
| auc | 0.98526 | nan |
| f1 | 0.965066 | 0.381407 |
| accuracy | 0.965066 | 0.381407 |
| precision | 1 | 0.965505 |
| recall | 1 | 8.07996e-12 |
| mcc | 0.930131 | 0.381407 |
| score | threshold | |
|---|---|---|
| logloss | 0.142061 | nan |
| auc | 0.98526 | nan |
| f1 | 0.965066 | 0.381407 |
| accuracy | 0.965066 | 0.381407 |
| precision | 0.965066 | 0.381407 |
| recall | 0.965066 | 0.381407 |
| mcc | 0.930131 | 0.381407 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
11.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.119728 | nan |
| auc | 0.98854 | nan |
| f1 | 0.964758 | 0.574991 |
| accuracy | 0.965066 | 0.574991 |
| precision | 1 | 0.988363 |
| recall | 1 | 2.18901e-09 |
| mcc | 0.930273 | 0.574991 |
| score | threshold | |
|---|---|---|
| logloss | 0.119728 | nan |
| auc | 0.98854 | nan |
| f1 | 0.964758 | 0.574991 |
| accuracy | 0.965066 | 0.574991 |
| precision | 0.973333 | 0.574991 |
| recall | 0.956332 | 0.574991 |
| mcc | 0.930273 | 0.574991 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
logloss
14.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.131008 | nan |
| auc | 0.98792 | nan |
| f1 | 0.965368 | 0.249998 |
| accuracy | 0.965066 | 0.249998 |
| precision | 1 | 0.943099 |
| recall | 1 | 4.0149e-09 |
| mcc | 0.930273 | 0.249998 |
| score | threshold | |
|---|---|---|
| logloss | 0.131008 | nan |
| auc | 0.98792 | nan |
| f1 | 0.965368 | 0.249998 |
| accuracy | 0.965066 | 0.249998 |
| precision | 0.957082 | 0.249998 |
| recall | 0.973799 | 0.249998 |
| mcc | 0.930273 | 0.249998 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
15.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.126845 | nan |
| auc | 0.986995 | nan |
| f1 | 0.964758 | 0.472262 |
| accuracy | 0.965066 | 0.472262 |
| precision | 1 | 0.968365 |
| recall | 1 | 3.19017e-08 |
| mcc | 0.930273 | 0.472262 |
| score | threshold | |
|---|---|---|
| logloss | 0.126845 | nan |
| auc | 0.986995 | nan |
| f1 | 0.964758 | 0.472262 |
| accuracy | 0.965066 | 0.472262 |
| precision | 0.973333 | 0.472262 |
| recall | 0.956332 | 0.472262 |
| mcc | 0.930273 | 0.472262 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
logloss
14.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.122106 | nan |
| auc | 0.989083 | nan |
| f1 | 0.969697 | 0.28944 |
| accuracy | 0.969432 | 0.28944 |
| precision | 1 | 0.941556 |
| recall | 1 | 2.72276e-13 |
| mcc | 0.939008 | 0.28944 |
| score | threshold | |
|---|---|---|
| logloss | 0.122106 | nan |
| auc | 0.989083 | nan |
| f1 | 0.969697 | 0.28944 |
| accuracy | 0.969432 | 0.28944 |
| precision | 0.961373 | 0.28944 |
| recall | 0.978166 | 0.28944 |
| mcc | 0.939008 | 0.28944 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 5 | 224 |
logloss
18.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.127732 | nan |
| auc | 0.987567 | nan |
| f1 | 0.965066 | 0.389129 |
| accuracy | 0.965066 | 0.389129 |
| precision | 1 | 0.98245 |
| recall | 1 | 1.15357e-09 |
| mcc | 0.930131 | 0.389129 |
| score | threshold | |
|---|---|---|
| logloss | 0.127732 | nan |
| auc | 0.987567 | nan |
| f1 | 0.965066 | 0.389129 |
| accuracy | 0.965066 | 0.389129 |
| precision | 0.965066 | 0.389129 |
| recall | 0.965066 | 0.389129 |
| mcc | 0.930131 | 0.389129 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
19.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.13886 | nan |
| auc | 0.985832 | nan |
| f1 | 0.961039 | 0.272588 |
| accuracy | 0.960699 | 0.272588 |
| precision | 1 | 0.974449 |
| recall | 1 | 1.06935e-11 |
| mcc | 0.921538 | 0.272588 |
| score | threshold | |
|---|---|---|
| logloss | 0.13886 | nan |
| auc | 0.985832 | nan |
| f1 | 0.961039 | 0.272588 |
| accuracy | 0.960699 | 0.272588 |
| precision | 0.95279 | 0.272588 |
| recall | 0.969432 | 0.272588 |
| mcc | 0.921538 | 0.272588 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 7 | 222 |
logloss
20.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.116853 | nan |
| auc | 0.989951 | nan |
| f1 | 0.961039 | 0.288601 |
| accuracy | 0.960699 | 0.288601 |
| precision | 1 | 0.982453 |
| recall | 1 | 1.40091e-07 |
| mcc | 0.921538 | 0.288601 |
| score | threshold | |
|---|---|---|
| logloss | 0.116853 | nan |
| auc | 0.989951 | nan |
| f1 | 0.961039 | 0.288601 |
| accuracy | 0.960699 | 0.288601 |
| precision | 0.95279 | 0.288601 |
| recall | 0.969432 | 0.288601 |
| mcc | 0.921538 | 0.288601 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 7 | 222 |
logloss
21.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.141791 | nan |
| auc | 0.985174 | nan |
| f1 | 0.969432 | 0.410127 |
| accuracy | 0.969432 | 0.410127 |
| precision | 1 | 0.96471 |
| recall | 1 | 1.65529e-11 |
| mcc | 0.938865 | 0.410127 |
| score | threshold | |
|---|---|---|
| logloss | 0.141791 | nan |
| auc | 0.985174 | nan |
| f1 | 0.969432 | 0.410127 |
| accuracy | 0.969432 | 0.410127 |
| precision | 0.969432 | 0.410127 |
| recall | 0.969432 | 0.410127 |
| mcc | 0.938865 | 0.410127 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
4.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.313541 | nan |
| auc | 0.95309 | nan |
| f1 | 0.924078 | 0.266667 |
| accuracy | 0.923581 | 0.266667 |
| precision | 0.994652 | 0.818182 |
| recall | 0.9869 | 0 |
| mcc | 0.849166 | 0.6875 |
| score | threshold | |
|---|---|---|
| logloss | 0.313541 | nan |
| auc | 0.95309 | nan |
| f1 | 0.924078 | 0.266667 |
| accuracy | 0.923581 | 0.266667 |
| precision | 0.918103 | 0.266667 |
| recall | 0.930131 | 0.266667 |
| mcc | 0.847234 | 0.266667 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 210 | 19 |
| Labeled as 1 | 16 | 213 |
logloss
34.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.111399 | nan |
| auc | 0.993745 | nan |
| f1 | 0.965665 | 0.113672 |
| accuracy | 0.965066 | 0.113672 |
| precision | 1 | 0.954733 |
| recall | 1 | 3.6781e-05 |
| mcc | 0.930699 | 0.113672 |
| score | threshold | |
|---|---|---|
| logloss | 0.111399 | nan |
| auc | 0.993745 | nan |
| f1 | 0.965665 | 0.113672 |
| accuracy | 0.965066 | 0.113672 |
| precision | 0.949367 | 0.113672 |
| recall | 0.982533 | 0.113672 |
| mcc | 0.930699 | 0.113672 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 4 | 225 |
logloss
21.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.116745 | nan |
| auc | 0.992582 | nan |
| f1 | 0.965368 | 0.206498 |
| accuracy | 0.965066 | 0.206498 |
| precision | 1 | 0.929169 |
| recall | 1 | 3.12795e-05 |
| mcc | 0.930273 | 0.206498 |
| score | threshold | |
|---|---|---|
| logloss | 0.116745 | nan |
| auc | 0.992582 | nan |
| f1 | 0.965368 | 0.206498 |
| accuracy | 0.965066 | 0.206498 |
| precision | 0.957082 | 0.206498 |
| recall | 0.973799 | 0.206498 |
| mcc | 0.930273 | 0.206498 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
19.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.109369 | nan |
| auc | 0.993326 | nan |
| f1 | 0.965665 | 0.114513 |
| accuracy | 0.965066 | 0.114513 |
| precision | 1 | 0.952774 |
| recall | 1 | 4.25201e-05 |
| mcc | 0.930699 | 0.114513 |
| score | threshold | |
|---|---|---|
| logloss | 0.109369 | nan |
| auc | 0.993326 | nan |
| f1 | 0.965665 | 0.114513 |
| accuracy | 0.965066 | 0.114513 |
| precision | 0.949367 | 0.114513 |
| recall | 0.982533 | 0.114513 |
| mcc | 0.930699 | 0.114513 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 4 | 225 |
logloss
27.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.111014 | nan |
| auc | 0.991095 | nan |
| f1 | 0.969432 | 0.222911 |
| accuracy | 0.969432 | 0.222911 |
| precision | 1 | 0.927431 |
| recall | 1 | 7.16241e-05 |
| mcc | 0.938865 | 0.222911 |
| score | threshold | |
|---|---|---|
| logloss | 0.111014 | nan |
| auc | 0.991095 | nan |
| f1 | 0.969432 | 0.222911 |
| accuracy | 0.969432 | 0.222911 |
| precision | 0.969432 | 0.222911 |
| recall | 0.969432 | 0.222911 |
| mcc | 0.938865 | 0.222911 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
19.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.11248 | nan |
| auc | 0.993421 | nan |
| f1 | 0.965665 | 0.158107 |
| accuracy | 0.965066 | 0.158107 |
| precision | 1 | 0.92678 |
| recall | 1 | 3.77887e-05 |
| mcc | 0.930699 | 0.158107 |
| score | threshold | |
|---|---|---|
| logloss | 0.11248 | nan |
| auc | 0.993421 | nan |
| f1 | 0.965665 | 0.158107 |
| accuracy | 0.965066 | 0.158107 |
| precision | 0.949367 | 0.158107 |
| recall | 0.982533 | 0.158107 |
| mcc | 0.930699 | 0.158107 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 4 | 225 |
logloss
18.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.101761 | nan |
| auc | 0.993154 | nan |
| f1 | 0.969432 | 0.332354 |
| accuracy | 0.969432 | 0.332354 |
| precision | 1 | 0.941953 |
| recall | 1 | 3.10927e-05 |
| mcc | 0.939008 | 0.476525 |
| score | threshold | |
|---|---|---|
| logloss | 0.101761 | nan |
| auc | 0.993154 | nan |
| f1 | 0.969432 | 0.332354 |
| accuracy | 0.969432 | 0.332354 |
| precision | 0.969432 | 0.332354 |
| recall | 0.969432 | 0.332354 |
| mcc | 0.938865 | 0.332354 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
32.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.105791 | nan |
| auc | 0.992029 | nan |
| f1 | 0.969432 | 0.314584 |
| accuracy | 0.969432 | 0.314584 |
| precision | 1 | 0.940397 |
| recall | 1 | 6.77433e-05 |
| mcc | 0.938865 | 0.314584 |
| score | threshold | |
|---|---|---|
| logloss | 0.105791 | nan |
| auc | 0.992029 | nan |
| f1 | 0.969432 | 0.314584 |
| accuracy | 0.969432 | 0.314584 |
| precision | 0.969432 | 0.314584 |
| recall | 0.969432 | 0.314584 |
| mcc | 0.938865 | 0.314584 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
31.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.100147 | nan |
| auc | 0.994527 | nan |
| f1 | 0.965368 | 0.193789 |
| accuracy | 0.965066 | 0.193789 |
| precision | 1 | 0.918829 |
| recall | 1 | 9.09971e-05 |
| mcc | 0.930273 | 0.193789 |
| score | threshold | |
|---|---|---|
| logloss | 0.100147 | nan |
| auc | 0.994527 | nan |
| f1 | 0.965368 | 0.193789 |
| accuracy | 0.965066 | 0.193789 |
| precision | 0.957082 | 0.193789 |
| recall | 0.973799 | 0.193789 |
| mcc | 0.930273 | 0.193789 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
17.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.115992 | nan |
| auc | 0.989512 | nan |
| f1 | 0.965066 | 0.291756 |
| accuracy | 0.965066 | 0.291756 |
| precision | 1 | 0.984286 |
| recall | 1 | 3.96694e-05 |
| mcc | 0.930131 | 0.291756 |
| score | threshold | |
|---|---|---|
| logloss | 0.115992 | nan |
| auc | 0.989512 | nan |
| f1 | 0.965066 | 0.291756 |
| accuracy | 0.965066 | 0.291756 |
| precision | 0.965066 | 0.291756 |
| recall | 0.965066 | 0.291756 |
| mcc | 0.930131 | 0.291756 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
50.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.114289 | nan |
| auc | 0.993574 | nan |
| f1 | 0.965066 | 0.304119 |
| accuracy | 0.965066 | 0.304119 |
| precision | 1 | 0.907739 |
| recall | 1 | 4.52382e-05 |
| mcc | 0.930273 | 0.465208 |
| score | threshold | |
|---|---|---|
| logloss | 0.114289 | nan |
| auc | 0.993574 | nan |
| f1 | 0.965066 | 0.304119 |
| accuracy | 0.965066 | 0.304119 |
| precision | 0.965066 | 0.304119 |
| recall | 0.965066 | 0.304119 |
| mcc | 0.930131 | 0.304119 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
26.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.11095 | nan |
| auc | 0.992716 | nan |
| f1 | 0.965368 | 0.179076 |
| accuracy | 0.965066 | 0.179076 |
| precision | 1 | 0.933231 |
| recall | 1 | 3.11459e-05 |
| mcc | 0.930273 | 0.179076 |
| score | threshold | |
|---|---|---|
| logloss | 0.11095 | nan |
| auc | 0.992716 | nan |
| f1 | 0.965368 | 0.179076 |
| accuracy | 0.965066 | 0.179076 |
| precision | 0.957082 | 0.179076 |
| recall | 0.973799 | 0.179076 |
| mcc | 0.930273 | 0.179076 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
42.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.109186 | nan |
| auc | 0.993173 | nan |
| f1 | 0.969432 | 0.348351 |
| accuracy | 0.969432 | 0.348351 |
| precision | 1 | 0.914185 |
| recall | 1 | 2.88539e-05 |
| mcc | 0.938865 | 0.348351 |
| score | threshold | |
|---|---|---|
| logloss | 0.109186 | nan |
| auc | 0.993173 | nan |
| f1 | 0.969432 | 0.348351 |
| accuracy | 0.969432 | 0.348351 |
| precision | 0.969432 | 0.348351 |
| recall | 0.969432 | 0.348351 |
| mcc | 0.938865 | 0.348351 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
36.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.10771 | nan |
| auc | 0.992201 | nan |
| f1 | 0.965066 | 0.240671 |
| accuracy | 0.965066 | 0.240671 |
| precision | 1 | 0.929047 |
| recall | 1 | 0.000146498 |
| mcc | 0.930131 | 0.240671 |
| score | threshold | |
|---|---|---|
| logloss | 0.10771 | nan |
| auc | 0.992201 | nan |
| f1 | 0.965066 | 0.240671 |
| accuracy | 0.965066 | 0.240671 |
| precision | 0.965066 | 0.240671 |
| recall | 0.965066 | 0.240671 |
| mcc | 0.930131 | 0.240671 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
50.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.096346 | nan |
| auc | 0.994317 | nan |
| f1 | 0.965368 | 0.186266 |
| accuracy | 0.965066 | 0.186266 |
| precision | 1 | 0.966721 |
| recall | 1 | 9.68604e-05 |
| mcc | 0.931411 | 0.761346 |
| score | threshold | |
|---|---|---|
| logloss | 0.096346 | nan |
| auc | 0.994317 | nan |
| f1 | 0.965368 | 0.186266 |
| accuracy | 0.965066 | 0.186266 |
| precision | 0.957082 | 0.186266 |
| recall | 0.973799 | 0.186266 |
| mcc | 0.930273 | 0.186266 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
12.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.204734 | nan |
| auc | 0.98033 | nan |
| f1 | 0.946188 | 0.591993 |
| accuracy | 0.947598 | 0.591993 |
| precision | 1 | 0.88944 |
| recall | 1 | 0.0182102 |
| mcc | 0.896428 | 0.591993 |
| score | threshold | |
|---|---|---|
| logloss | 0.204734 | nan |
| auc | 0.98033 | nan |
| f1 | 0.946188 | 0.591993 |
| accuracy | 0.947598 | 0.591993 |
| precision | 0.97235 | 0.591993 |
| recall | 0.921397 | 0.591993 |
| mcc | 0.896428 | 0.591993 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 18 | 211 |
logloss
4.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.313541 | nan |
| auc | 0.95309 | nan |
| f1 | 0.924078 | 0.266667 |
| accuracy | 0.923581 | 0.266667 |
| precision | 0.994652 | 0.818182 |
| recall | 0.9869 | 0 |
| mcc | 0.849166 | 0.6875 |
| score | threshold | |
|---|---|---|
| logloss | 0.313541 | nan |
| auc | 0.95309 | nan |
| f1 | 0.924078 | 0.266667 |
| accuracy | 0.923581 | 0.266667 |
| precision | 0.918103 | 0.266667 |
| recall | 0.930131 | 0.266667 |
| mcc | 0.847234 | 0.266667 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 210 | 19 |
| Labeled as 1 | 16 | 213 |
logloss
15.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.213752 | nan |
| auc | 0.98239 | nan |
| f1 | 0.955947 | 0.565679 |
| accuracy | 0.956332 | 0.565679 |
| precision | 1 | 0.728717 |
| recall | 1 | 0 |
| mcc | 0.912803 | 0.565679 |
| score | threshold | |
|---|---|---|
| logloss | 0.213752 | nan |
| auc | 0.98239 | nan |
| f1 | 0.955947 | 0.565679 |
| accuracy | 0.956332 | 0.565679 |
| precision | 0.964444 | 0.565679 |
| recall | 0.947598 | 0.565679 |
| mcc | 0.912803 | 0.565679 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 12 | 217 |
logloss
15.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.253847 | nan |
| auc | 0.966744 | nan |
| f1 | 0.9163 | 0.527316 |
| accuracy | 0.917031 | 0.527316 |
| precision | 1 | 0.828121 |
| recall | 1 | 0.0240841 |
| mcc | 0.834188 | 0.527316 |
| score | threshold | |
|---|---|---|
| logloss | 0.253847 | nan |
| auc | 0.966744 | nan |
| f1 | 0.9163 | 0.527316 |
| accuracy | 0.917031 | 0.527316 |
| precision | 0.924444 | 0.527316 |
| recall | 0.908297 | 0.527316 |
| mcc | 0.834188 | 0.527316 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 212 | 17 |
| Labeled as 1 | 21 | 208 |
logloss
18.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.277495 | nan |
| auc | 0.966257 | nan |
| f1 | 0.906122 | 0.501412 |
| accuracy | 0.90393 | 0.603984 |
| precision | 1 | 0.830827 |
| recall | 1 | 0 |
| mcc | 0.808354 | 0.603984 |
| score | threshold | |
|---|---|---|
| logloss | 0.277495 | nan |
| auc | 0.966257 | nan |
| f1 | 0.905579 | 0.603984 |
| accuracy | 0.90393 | 0.603984 |
| precision | 0.890295 | 0.603984 |
| recall | 0.921397 | 0.603984 |
| mcc | 0.808354 | 0.603984 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 203 | 26 |
| Labeled as 1 | 18 | 211 |
logloss
17.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.27513 | nan |
| auc | 0.967535 | nan |
| f1 | 0.917749 | 0.624172 |
| accuracy | 0.917031 | 0.624172 |
| precision | 1 | 0.870794 |
| recall | 1 | 0.0300446 |
| mcc | 0.834188 | 0.624172 |
| score | threshold | |
|---|---|---|
| logloss | 0.27513 | nan |
| auc | 0.967535 | nan |
| f1 | 0.917749 | 0.624172 |
| accuracy | 0.917031 | 0.624172 |
| precision | 0.909871 | 0.624172 |
| recall | 0.925764 | 0.624172 |
| mcc | 0.834188 | 0.624172 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 208 | 21 |
| Labeled as 1 | 17 | 212 |
logloss
18.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.261804 | nan |
| auc | 0.970586 | nan |
| f1 | 0.907923 | 0.504539 |
| accuracy | 0.906114 | 0.504539 |
| precision | 1 | 0.92 |
| recall | 0.995633 | 0 |
| mcc | 0.812855 | 0.504539 |
| score | threshold | |
|---|---|---|
| logloss | 0.261804 | nan |
| auc | 0.970586 | nan |
| f1 | 0.907923 | 0.504539 |
| accuracy | 0.906114 | 0.504539 |
| precision | 0.890756 | 0.504539 |
| recall | 0.925764 | 0.504539 |
| mcc | 0.812855 | 0.504539 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 203 | 26 |
| Labeled as 1 | 17 | 212 |
logloss
21.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.235061 | nan |
| auc | 0.974981 | nan |
| f1 | 0.914661 | 0.584058 |
| accuracy | 0.919214 | 0.651184 |
| precision | 1 | 0.766599 |
| recall | 1 | 0 |
| mcc | 0.845233 | 0.651184 |
| score | threshold | |
|---|---|---|
| logloss | 0.235061 | nan |
| auc | 0.974981 | nan |
| f1 | 0.913753 | 0.651184 |
| accuracy | 0.919214 | 0.651184 |
| precision | 0.98 | 0.651184 |
| recall | 0.855895 | 0.651184 |
| mcc | 0.845233 | 0.651184 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 225 | 4 |
| Labeled as 1 | 33 | 196 |
logloss
22.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.195568 | nan |
| auc | 0.98259 | nan |
| f1 | 0.938326 | 0.548485 |
| accuracy | 0.938865 | 0.548485 |
| precision | 1 | 0.870801 |
| recall | 1 | 0.00604027 |
| mcc | 0.877863 | 0.548485 |
| score | threshold | |
|---|---|---|
| logloss | 0.195568 | nan |
| auc | 0.98259 | nan |
| f1 | 0.938326 | 0.548485 |
| accuracy | 0.938865 | 0.548485 |
| precision | 0.946667 | 0.548485 |
| recall | 0.930131 | 0.548485 |
| mcc | 0.877863 | 0.548485 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 16 | 213 |
logloss
23.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.276271 | nan |
| auc | 0.963187 | nan |
| f1 | 0.904232 | 0.594512 |
| accuracy | 0.906114 | 0.594512 |
| precision | 1 | 0.839506 |
| recall | 1 | 0 |
| mcc | 0.812855 | 0.594512 |
| score | threshold | |
|---|---|---|
| logloss | 0.276271 | nan |
| auc | 0.963187 | nan |
| f1 | 0.904232 | 0.594512 |
| accuracy | 0.906114 | 0.594512 |
| precision | 0.922727 | 0.594512 |
| recall | 0.886463 | 0.594512 |
| mcc | 0.812855 | 0.594512 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 212 | 17 |
| Labeled as 1 | 26 | 203 |
logloss
12.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.184721 | nan |
| auc | 0.979911 | nan |
| f1 | 0.942222 | 0.505854 |
| accuracy | 0.943231 | 0.505854 |
| precision | 1 | 0.90721 |
| recall | 1 | 0.0248473 |
| mcc | 0.887004 | 0.505854 |
| score | threshold | |
|---|---|---|
| logloss | 0.184721 | nan |
| auc | 0.979911 | nan |
| f1 | 0.942222 | 0.505854 |
| accuracy | 0.943231 | 0.505854 |
| precision | 0.959276 | 0.505854 |
| recall | 0.925764 | 0.505854 |
| mcc | 0.887004 | 0.505854 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 17 | 212 |
logloss
13.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.179832 | nan |
| auc | 0.984259 | nan |
| f1 | 0.946667 | 0.532058 |
| accuracy | 0.947598 | 0.532058 |
| precision | 1 | 0.842339 |
| recall | 1 | 0 |
| mcc | 0.895743 | 0.532058 |
| score | threshold | |
|---|---|---|
| logloss | 0.179832 | nan |
| auc | 0.984259 | nan |
| f1 | 0.946667 | 0.532058 |
| accuracy | 0.947598 | 0.532058 |
| precision | 0.963801 | 0.532058 |
| recall | 0.930131 | 0.532058 |
| mcc | 0.895743 | 0.532058 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 16 | 213 |
logloss
5.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.18766 | nan |
| auc | 0.974447 | nan |
| f1 | 0.941176 | 0.526158 |
| accuracy | 0.943231 | 0.526158 |
| precision | 1 | 0.89985 |
| recall | 1 | 0.00736128 |
| mcc | 0.888635 | 0.526158 |
| score | threshold | |
|---|---|---|
| logloss | 0.18766 | nan |
| auc | 0.974447 | nan |
| f1 | 0.941176 | 0.526158 |
| accuracy | 0.943231 | 0.526158 |
| precision | 0.976526 | 0.526158 |
| recall | 0.908297 | 0.526158 |
| mcc | 0.888635 | 0.526158 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 224 | 5 |
| Labeled as 1 | 21 | 208 |
logloss
15.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.254352 | nan |
| auc | 0.961023 | nan |
| f1 | 0.911894 | 0.56382 |
| accuracy | 0.912664 | 0.56382 |
| precision | 1 | 0.84058 |
| recall | 1 | 0.0372174 |
| mcc | 0.825453 | 0.56382 |
| score | threshold | |
|---|---|---|
| logloss | 0.254352 | nan |
| auc | 0.961023 | nan |
| f1 | 0.911894 | 0.56382 |
| accuracy | 0.912664 | 0.56382 |
| precision | 0.92 | 0.56382 |
| recall | 0.90393 | 0.56382 |
| mcc | 0.825453 | 0.56382 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 211 | 18 |
| Labeled as 1 | 22 | 207 |
logloss
16.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.216421 | nan |
| auc | 0.978299 | nan |
| f1 | 0.932127 | 0.562217 |
| accuracy | 0.934498 | 0.562217 |
| precision | 1 | 0.666805 |
| recall | 1 | 0 |
| mcc | 0.873808 | 0.611616 |
| score | threshold | |
|---|---|---|
| logloss | 0.216421 | nan |
| auc | 0.978299 | nan |
| f1 | 0.932127 | 0.562217 |
| accuracy | 0.934498 | 0.562217 |
| precision | 0.967136 | 0.562217 |
| recall | 0.899563 | 0.562217 |
| mcc | 0.871125 | 0.562217 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 23 | 206 |
logloss
18.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.240711 | nan |
| auc | 0.970538 | nan |
| f1 | 0.905077 | 0.602949 |
| accuracy | 0.908297 | 0.677061 |
| precision | 1 | 0.764972 |
| recall | 1 | 0.028125 |
| mcc | 0.821116 | 0.677061 |
| score | threshold | |
|---|---|---|
| logloss | 0.240711 | nan |
| auc | 0.970538 | nan |
| f1 | 0.903226 | 0.677061 |
| accuracy | 0.908297 | 0.677061 |
| precision | 0.956098 | 0.677061 |
| recall | 0.855895 | 0.677061 |
| mcc | 0.821116 | 0.677061 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 33 | 196 |
logloss
22.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.299218 | nan |
| auc | 0.952251 | nan |
| f1 | 0.874459 | 0.51087 |
| accuracy | 0.873362 | 0.51087 |
| precision | 1 | 0.6875 |
| recall | 0.991266 | 0 |
| mcc | 0.748383 | 0.594595 |
| score | threshold | |
|---|---|---|
| logloss | 0.299218 | nan |
| auc | 0.952251 | nan |
| f1 | 0.874459 | 0.51087 |
| accuracy | 0.873362 | 0.51087 |
| precision | 0.866953 | 0.51087 |
| recall | 0.882096 | 0.51087 |
| mcc | 0.746839 | 0.51087 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 198 | 31 |
| Labeled as 1 | 27 | 202 |
logloss
20.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.220836 | nan |
| auc | 0.968384 | nan |
| f1 | 0.909931 | 0.568462 |
| accuracy | 0.914847 | 0.568462 |
| precision | 1 | 0.720656 |
| recall | 1 | 0.00612245 |
| mcc | 0.834683 | 0.568462 |
| score | threshold | |
|---|---|---|
| logloss | 0.220836 | nan |
| auc | 0.968384 | nan |
| f1 | 0.909931 | 0.568462 |
| accuracy | 0.914847 | 0.568462 |
| precision | 0.965686 | 0.568462 |
| recall | 0.860262 | 0.568462 |
| mcc | 0.834683 | 0.568462 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 32 | 197 |
logloss
21.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.175504 | nan |
| auc | 0.980044 | nan |
| f1 | 0.946188 | 0.53778 |
| accuracy | 0.947598 | 0.53778 |
| precision | 1 | 0.768968 |
| recall | 1 | 0.0182112 |
| mcc | 0.89739 | 0.56918 |
| score | threshold | |
|---|---|---|
| logloss | 0.175504 | nan |
| auc | 0.980044 | nan |
| f1 | 0.946188 | 0.53778 |
| accuracy | 0.947598 | 0.53778 |
| precision | 0.97235 | 0.53778 |
| recall | 0.921397 | 0.53778 |
| mcc | 0.896428 | 0.53778 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 18 | 211 |
logloss
9.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.254356 | nan |
| auc | 0.970967 | nan |
| f1 | 0.928251 | 0.645626 |
| accuracy | 0.930131 | 0.645626 |
| precision | 0.990826 | 0.997606 |
| recall | 1 | 8.06644e-13 |
| mcc | 0.862369 | 0.678609 |
| score | threshold | |
|---|---|---|
| logloss | 0.254356 | nan |
| auc | 0.970967 | nan |
| f1 | 0.928251 | 0.645626 |
| accuracy | 0.930131 | 0.645626 |
| precision | 0.953917 | 0.645626 |
| recall | 0.90393 | 0.645626 |
| mcc | 0.861446 | 0.645626 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 22 | 207 |
logloss
11.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.164998 | nan |
| auc | 0.980225 | nan |
| f1 | 0.951111 | 0.461609 |
| accuracy | 0.951965 | 0.461609 |
| precision | 1 | 0.975285 |
| recall | 1 | 0.000176863 |
| mcc | 0.904482 | 0.461609 |
| score | threshold | |
|---|---|---|
| logloss | 0.164998 | nan |
| auc | 0.980225 | nan |
| f1 | 0.951111 | 0.461609 |
| accuracy | 0.951965 | 0.461609 |
| precision | 0.968326 | 0.461609 |
| recall | 0.934498 | 0.461609 |
| mcc | 0.904482 | 0.461609 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 15 | 214 |
logloss
13.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.147187 | nan |
| auc | 0.987338 | nan |
| f1 | 0.951965 | 0.451893 |
| accuracy | 0.951965 | 0.451893 |
| precision | 1 | 0.985423 |
| recall | 1 | 3.41977e-12 |
| mcc | 0.904068 | 0.530699 |
| score | threshold | |
|---|---|---|
| logloss | 0.147187 | nan |
| auc | 0.987338 | nan |
| f1 | 0.951965 | 0.451893 |
| accuracy | 0.951965 | 0.451893 |
| precision | 0.951965 | 0.451893 |
| recall | 0.951965 | 0.451893 |
| mcc | 0.90393 | 0.451893 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 11 | 218 |
logloss
10.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.125001 | nan |
| auc | 0.988406 | nan |
| f1 | 0.960699 | 0.315884 |
| accuracy | 0.960699 | 0.315884 |
| precision | 1 | 0.968999 |
| recall | 1 | 2.95526e-08 |
| mcc | 0.92196 | 0.600659 |
| score | threshold | |
|---|---|---|
| logloss | 0.125001 | nan |
| auc | 0.988406 | nan |
| f1 | 0.960699 | 0.315884 |
| accuracy | 0.960699 | 0.315884 |
| precision | 0.960699 | 0.315884 |
| recall | 0.960699 | 0.315884 |
| mcc | 0.921397 | 0.315884 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
logloss
14.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.248498 | nan |
| auc | 0.968231 | nan |
| f1 | 0.942731 | 0.512363 |
| accuracy | 0.943231 | 0.512363 |
| precision | 1 | 0.999773 |
| recall | 1 | 1.51059e-07 |
| mcc | 0.886598 | 0.512363 |
| score | threshold | |
|---|---|---|
| logloss | 0.248498 | nan |
| auc | 0.968231 | nan |
| f1 | 0.942731 | 0.512363 |
| accuracy | 0.943231 | 0.512363 |
| precision | 0.951111 | 0.512363 |
| recall | 0.934498 | 0.512363 |
| mcc | 0.886598 | 0.512363 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 218 | 11 |
| Labeled as 1 | 15 | 214 |
logloss
15.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.228268 | nan |
| auc | 0.96968 | nan |
| f1 | 0.938865 | 0.493045 |
| accuracy | 0.938865 | 0.493045 |
| precision | 1 | 0.938936 |
| recall | 1 | 0.000390025 |
| mcc | 0.877729 | 0.493045 |
| score | threshold | |
|---|---|---|
| logloss | 0.228268 | nan |
| auc | 0.96968 | nan |
| f1 | 0.938865 | 0.493045 |
| accuracy | 0.938865 | 0.493045 |
| precision | 0.938865 | 0.493045 |
| recall | 0.938865 | 0.493045 |
| mcc | 0.877729 | 0.493045 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 215 | 14 |
| Labeled as 1 | 14 | 215 |
logloss
17.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.176633 | nan |
| auc | 0.981179 | nan |
| f1 | 0.951111 | 0.492894 |
| accuracy | 0.951965 | 0.492894 |
| precision | 1 | 0.955953 |
| recall | 1 | 0.000721177 |
| mcc | 0.904482 | 0.492894 |
| score | threshold | |
|---|---|---|
| logloss | 0.176633 | nan |
| auc | 0.981179 | nan |
| f1 | 0.951111 | 0.492894 |
| accuracy | 0.951965 | 0.492894 |
| precision | 0.968326 | 0.492894 |
| recall | 0.934498 | 0.492894 |
| mcc | 0.904482 | 0.492894 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 15 | 214 |
logloss
17.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.21853 | nan |
| auc | 0.970576 | nan |
| f1 | 0.932735 | 0.50103 |
| accuracy | 0.934498 | 0.50103 |
| precision | 1 | 0.988246 |
| recall | 1 | 4.8378e-05 |
| mcc | 0.870191 | 0.50103 |
| score | threshold | |
|---|---|---|
| logloss | 0.21853 | nan |
| auc | 0.970576 | nan |
| f1 | 0.932735 | 0.50103 |
| accuracy | 0.934498 | 0.50103 |
| precision | 0.958525 | 0.50103 |
| recall | 0.908297 | 0.50103 |
| mcc | 0.870191 | 0.50103 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 21 | 208 |
logloss
20.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.188742 | nan |
| auc | 0.977804 | nan |
| f1 | 0.947137 | 0.352946 |
| accuracy | 0.947598 | 0.352946 |
| precision | 1 | 0.996697 |
| recall | 1 | 1.21043e-08 |
| mcc | 0.895333 | 0.352946 |
| score | threshold | |
|---|---|---|
| logloss | 0.188742 | nan |
| auc | 0.977804 | nan |
| f1 | 0.947137 | 0.352946 |
| accuracy | 0.947598 | 0.352946 |
| precision | 0.955556 | 0.352946 |
| recall | 0.938865 | 0.352946 |
| mcc | 0.895333 | 0.352946 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 14 | 215 |
logloss
9.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.977941 | 0.857143 |
| recall | 0.969432 | 0 |
| mcc | 0.877763 | 0.142857 |
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.935065 | 0.142857 |
| recall | 0.943231 | 0.142857 |
| mcc | 0.877763 | 0.142857 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 13 | 216 |
logloss
10.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.437341 | nan |
| auc | 0.972302 | nan |
| f1 | 0.95279 | 0 |
| accuracy | 0.951965 | 0 |
| precision | 0.984127 | 0.767059 |
| recall | 0.969432 | 0 |
| mcc | 0.904482 | 0 |
| score | threshold | |
|---|---|---|
| logloss | 0.437341 | nan |
| auc | 0.972302 | nan |
| f1 | 0.95279 | 0 |
| accuracy | 0.951965 | 0 |
| precision | 0.936709 | 0 |
| recall | 0.969432 | 0 |
| mcc | 0.904482 | 0 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 7 | 222 |
logloss
11.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.437341 | nan |
| auc | 0.972302 | nan |
| f1 | 0.95279 | 0 |
| accuracy | 0.951965 | 0 |
| precision | 0.984127 | 0.767059 |
| recall | 0.969432 | 0 |
| mcc | 0.904482 | 0 |
| score | threshold | |
|---|---|---|
| logloss | 0.437341 | nan |
| auc | 0.972302 | nan |
| f1 | 0.95279 | 0 |
| accuracy | 0.951965 | 0 |
| precision | 0.936709 | 0 |
| recall | 0.969432 | 0 |
| mcc | 0.904482 | 0 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 7 | 222 |
logloss
13.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.977941 | 0.857143 |
| recall | 0.969432 | 0 |
| mcc | 0.877763 | 0.142857 |
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.935065 | 0.142857 |
| recall | 0.943231 | 0.142857 |
| mcc | 0.877763 | 0.142857 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 13 | 216 |
logloss
8.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.132326 | nan |
| auc | 0.987662 | nan |
| f1 | 0.960699 | 0.343988 |
| accuracy | 0.960699 | 0.343988 |
| precision | 1 | 0.959947 |
| recall | 1 | 7.45871e-06 |
| mcc | 0.921538 | 0.420318 |
| score | threshold | |
|---|---|---|
| logloss | 0.132326 | nan |
| auc | 0.987662 | nan |
| f1 | 0.960699 | 0.343988 |
| accuracy | 0.960699 | 0.343988 |
| precision | 0.960699 | 0.343988 |
| recall | 0.960699 | 0.343988 |
| mcc | 0.921397 | 0.343988 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
logloss
15.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.507229 | nan |
| auc | 0.968269 | nan |
| f1 | 0.960699 | 0 |
| accuracy | 0.960699 | 0 |
| precision | 0.978495 | 0.666667 |
| recall | 0.960699 | 0 |
| mcc | 0.921397 | 0 |
| score | threshold | |
|---|---|---|
| logloss | 0.507229 | nan |
| auc | 0.968269 | nan |
| f1 | 0.960699 | 0 |
| accuracy | 0.960699 | 0 |
| precision | 0.960699 | 0 |
| recall | 0.960699 | 0 |
| mcc | 0.921397 | 0 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
logloss
16.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.977941 | 0.857143 |
| recall | 0.969432 | 0 |
| mcc | 0.877763 | 0.142857 |
| score | threshold | |
|---|---|---|
| logloss | 0.488837 | nan |
| auc | 0.966267 | nan |
| f1 | 0.93913 | 0.142857 |
| accuracy | 0.938865 | 0.142857 |
| precision | 0.935065 | 0.142857 |
| recall | 0.943231 | 0.142857 |
| mcc | 0.877763 | 0.142857 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 13 | 216 |
logloss
17.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.489052 | nan |
| auc | 0.969585 | nan |
| f1 | 0.960699 | 0 |
| accuracy | 0.960699 | 0 |
| precision | 0.981221 | 0.693078 |
| recall | 0.960699 | 0 |
| mcc | 0.921397 | 0 |
| score | threshold | |
|---|---|---|
| logloss | 0.489052 | nan |
| auc | 0.969585 | nan |
| f1 | 0.960699 | 0 |
| accuracy | 0.960699 | 0 |
| precision | 0.960699 | 0 |
| recall | 0.960699 | 0 |
| mcc | 0.921397 | 0 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 9 | 220 |
logloss
45.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.0992113 | nan |
| auc | 0.994546 | nan |
| f1 | 0.969432 | 0.244296 |
| accuracy | 0.969432 | 0.244296 |
| precision | 1 | 0.951536 |
| recall | 1 | 0.000125997 |
| mcc | 0.938865 | 0.244296 |
| score | threshold | |
|---|---|---|
| logloss | 0.0992113 | nan |
| auc | 0.994546 | nan |
| f1 | 0.969432 | 0.244296 |
| accuracy | 0.969432 | 0.244296 |
| precision | 0.969432 | 0.244296 |
| recall | 0.969432 | 0.244296 |
| mcc | 0.938865 | 0.244296 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
75.9 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.0989191 | nan |
| auc | 0.994413 | nan |
| f1 | 0.965066 | 0.323457 |
| accuracy | 0.965066 | 0.323457 |
| precision | 1 | 0.965657 |
| recall | 1 | 0.000109748 |
| mcc | 0.930699 | 0.67373 |
| score | threshold | |
|---|---|---|
| logloss | 0.0989191 | nan |
| auc | 0.994413 | nan |
| f1 | 0.965066 | 0.323457 |
| accuracy | 0.965066 | 0.323457 |
| precision | 0.965066 | 0.323457 |
| recall | 0.965066 | 0.323457 |
| mcc | 0.930131 | 0.323457 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
31.5 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.099829 | nan |
| auc | 0.994642 | nan |
| f1 | 0.965368 | 0.150459 |
| accuracy | 0.965066 | 0.150459 |
| precision | 1 | 0.967171 |
| recall | 1 | 5.35698e-05 |
| mcc | 0.930699 | 0.758612 |
| score | threshold | |
|---|---|---|
| logloss | 0.099829 | nan |
| auc | 0.994642 | nan |
| f1 | 0.965368 | 0.150459 |
| accuracy | 0.965066 | 0.150459 |
| precision | 0.957082 | 0.150459 |
| recall | 0.973799 | 0.150459 |
| mcc | 0.930273 | 0.150459 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
38.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.098331 | nan |
| auc | 0.994603 | nan |
| f1 | 0.969697 | 0.189577 |
| accuracy | 0.969432 | 0.189577 |
| precision | 1 | 0.896178 |
| recall | 1 | 4.40186e-05 |
| mcc | 0.939008 | 0.189577 |
| score | threshold | |
|---|---|---|
| logloss | 0.098331 | nan |
| auc | 0.994603 | nan |
| f1 | 0.969697 | 0.189577 |
| accuracy | 0.969432 | 0.189577 |
| precision | 0.961373 | 0.189577 |
| recall | 0.978166 | 0.189577 |
| mcc | 0.939008 | 0.189577 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 5 | 224 |
logloss
24.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.105146 | nan |
| auc | 0.992487 | nan |
| f1 | 0.969432 | 0.26613 |
| accuracy | 0.969432 | 0.26613 |
| precision | 1 | 0.943407 |
| recall | 1 | 2.1271e-05 |
| mcc | 0.938865 | 0.26613 |
| score | threshold | |
|---|---|---|
| logloss | 0.105146 | nan |
| auc | 0.992487 | nan |
| f1 | 0.969432 | 0.26613 |
| accuracy | 0.969432 | 0.26613 |
| precision | 0.969432 | 0.26613 |
| recall | 0.969432 | 0.26613 |
| mcc | 0.938865 | 0.26613 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 7 | 222 |
logloss
30.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.11485 | nan |
| auc | 0.991362 | nan |
| f1 | 0.965066 | 0.258872 |
| accuracy | 0.965066 | 0.258872 |
| precision | 1 | 0.91796 |
| recall | 1 | 2.42849e-05 |
| mcc | 0.930273 | 0.434036 |
| score | threshold | |
|---|---|---|
| logloss | 0.11485 | nan |
| auc | 0.991362 | nan |
| f1 | 0.965066 | 0.258872 |
| accuracy | 0.965066 | 0.258872 |
| precision | 0.965066 | 0.258872 |
| recall | 0.965066 | 0.258872 |
| mcc | 0.930131 | 0.258872 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
23.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.123575 | nan |
| auc | 0.987653 | nan |
| f1 | 0.964758 | 0.480689 |
| accuracy | 0.965066 | 0.480689 |
| precision | 1 | 0.982776 |
| recall | 1 | 4.9947e-08 |
| mcc | 0.930273 | 0.480689 |
| score | threshold | |
|---|---|---|
| logloss | 0.123575 | nan |
| auc | 0.987653 | nan |
| f1 | 0.964758 | 0.480689 |
| accuracy | 0.965066 | 0.480689 |
| precision | 0.973333 | 0.480689 |
| recall | 0.956332 | 0.480689 |
| mcc | 0.930273 | 0.480689 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
logloss
10.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.114824 | nan |
| auc | 0.990599 | nan |
| f1 | 0.965066 | 0.366157 |
| accuracy | 0.965066 | 0.366157 |
| precision | 1 | 0.920376 |
| recall | 1 | 1.90849e-05 |
| mcc | 0.930273 | 0.480957 |
| score | threshold | |
|---|---|---|
| logloss | 0.114824 | nan |
| auc | 0.990599 | nan |
| f1 | 0.965066 | 0.366157 |
| accuracy | 0.965066 | 0.366157 |
| precision | 0.965066 | 0.366157 |
| recall | 0.965066 | 0.366157 |
| mcc | 0.930131 | 0.366157 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
26.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.119156 | nan |
| auc | 0.989646 | nan |
| f1 | 0.960352 | 0.512618 |
| accuracy | 0.960699 | 0.512618 |
| precision | 1 | 0.981393 |
| recall | 1 | 4.41866e-07 |
| mcc | 0.92196 | 0.609892 |
| score | threshold | |
|---|---|---|
| logloss | 0.119156 | nan |
| auc | 0.989646 | nan |
| f1 | 0.960352 | 0.512618 |
| accuracy | 0.960699 | 0.512618 |
| precision | 0.968889 | 0.512618 |
| recall | 0.951965 | 0.512618 |
| mcc | 0.921538 | 0.512618 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 222 | 7 |
| Labeled as 1 | 11 | 218 |
logloss
25.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.117737 | nan |
| auc | 0.988921 | nan |
| f1 | 0.965066 | 0.306924 |
| accuracy | 0.965066 | 0.306924 |
| precision | 1 | 0.988074 |
| recall | 1 | 2.18611e-09 |
| mcc | 0.930273 | 0.574991 |
| score | threshold | |
|---|---|---|
| logloss | 0.117737 | nan |
| auc | 0.988921 | nan |
| f1 | 0.965066 | 0.306924 |
| accuracy | 0.965066 | 0.306924 |
| precision | 0.965066 | 0.306924 |
| recall | 0.965066 | 0.306924 |
| mcc | 0.930131 | 0.306924 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 8 | 221 |
logloss
24.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.119728 | nan |
| auc | 0.98854 | nan |
| f1 | 0.964758 | 0.574991 |
| accuracy | 0.965066 | 0.574991 |
| precision | 1 | 0.988363 |
| recall | 1 | 2.18901e-09 |
| mcc | 0.930273 | 0.574991 |
| score | threshold | |
|---|---|---|
| logloss | 0.119728 | nan |
| auc | 0.98854 | nan |
| f1 | 0.964758 | 0.574991 |
| accuracy | 0.965066 | 0.574991 |
| precision | 0.973333 | 0.574991 |
| recall | 0.956332 | 0.574991 |
| mcc | 0.930273 | 0.574991 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 223 | 6 |
| Labeled as 1 | 10 | 219 |
logloss
40.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.0934722 | nan |
| auc | 0.994928 | nan |
| f1 | 0.965368 | 0.179647 |
| accuracy | 0.965066 | 0.179647 |
| precision | 1 | 0.964811 |
| recall | 1 | 9.6435e-05 |
| mcc | 0.930699 | 0.653869 |
| score | threshold | |
|---|---|---|
| logloss | 0.0934722 | nan |
| auc | 0.994928 | nan |
| f1 | 0.965368 | 0.179647 |
| accuracy | 0.965066 | 0.179647 |
| precision | 0.957082 | 0.179647 |
| recall | 0.973799 | 0.179647 |
| mcc | 0.930273 | 0.179647 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
44.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.0933352 | nan |
| auc | 0.995061 | nan |
| f1 | 0.969697 | 0.171493 |
| accuracy | 0.969432 | 0.171493 |
| precision | 1 | 0.954979 |
| recall | 1 | 0.000102049 |
| mcc | 0.939008 | 0.171493 |
| score | threshold | |
|---|---|---|
| logloss | 0.0933352 | nan |
| auc | 0.995061 | nan |
| f1 | 0.969697 | 0.171493 |
| accuracy | 0.969432 | 0.171493 |
| precision | 0.961373 | 0.171493 |
| recall | 0.978166 | 0.171493 |
| mcc | 0.939008 | 0.171493 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 5 | 224 |
logloss
50.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.103991 | nan |
| auc | 0.993898 | nan |
| f1 | 0.965368 | 0.186038 |
| accuracy | 0.965066 | 0.186038 |
| precision | 1 | 0.967955 |
| recall | 1 | 4.12257e-05 |
| mcc | 0.930273 | 0.186038 |
| score | threshold | |
|---|---|---|
| logloss | 0.103991 | nan |
| auc | 0.993898 | nan |
| f1 | 0.965368 | 0.186038 |
| accuracy | 0.965066 | 0.186038 |
| precision | 0.957082 | 0.186038 |
| recall | 0.973799 | 0.186038 |
| mcc | 0.930273 | 0.186038 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
32.7 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.10591 | nan |
| auc | 0.993221 | nan |
| f1 | 0.969697 | 0.204454 |
| accuracy | 0.969432 | 0.204454 |
| precision | 1 | 0.98607 |
| recall | 1 | 4.16019e-05 |
| mcc | 0.939008 | 0.204454 |
| score | threshold | |
|---|---|---|
| logloss | 0.10591 | nan |
| auc | 0.993221 | nan |
| f1 | 0.969697 | 0.204454 |
| accuracy | 0.969432 | 0.204454 |
| precision | 0.961373 | 0.204454 |
| recall | 0.978166 | 0.204454 |
| mcc | 0.939008 | 0.204454 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 220 | 9 |
| Labeled as 1 | 5 | 224 |
logloss
57.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.0964026 | nan |
| auc | 0.995137 | nan |
| f1 | 0.965368 | 0.20728 |
| accuracy | 0.965066 | 0.20728 |
| precision | 1 | 0.959643 |
| recall | 1 | 6.94756e-05 |
| mcc | 0.930699 | 0.632217 |
| score | threshold | |
|---|---|---|
| logloss | 0.0964026 | nan |
| auc | 0.995137 | nan |
| f1 | 0.965368 | 0.20728 |
| accuracy | 0.965066 | 0.20728 |
| precision | 0.957082 | 0.20728 |
| recall | 0.973799 | 0.20728 |
| mcc | 0.930273 | 0.20728 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 219 | 10 |
| Labeled as 1 | 6 | 223 |
logloss
7.6 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.187465 | nan |
| auc | 0.977594 | nan |
| f1 | 0.946667 | 0.440257 |
| accuracy | 0.947598 | 0.440257 |
| precision | 1 | 0.999284 |
| recall | 1 | 1.70169e-06 |
| mcc | 0.895743 | 0.440257 |
| score | threshold | |
|---|---|---|
| logloss | 0.187465 | nan |
| auc | 0.977594 | nan |
| f1 | 0.946667 | 0.440257 |
| accuracy | 0.947598 | 0.440257 |
| precision | 0.963801 | 0.440257 |
| recall | 0.930131 | 0.440257 |
| mcc | 0.895743 | 0.440257 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 221 | 8 |
| Labeled as 1 | 16 | 213 |
logloss
11.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.228603 | nan |
| auc | 0.976421 | nan |
| f1 | 0.929825 | 0.528751 |
| accuracy | 0.930131 | 0.528751 |
| precision | 1 | 0.752055 |
| recall | 1 | 0.0077059 |
| mcc | 0.860295 | 0.528751 |
| score | threshold | |
|---|---|---|
| logloss | 0.228603 | nan |
| auc | 0.976421 | nan |
| f1 | 0.929825 | 0.528751 |
| accuracy | 0.930131 | 0.528751 |
| precision | 0.933921 | 0.528751 |
| recall | 0.925764 | 0.528751 |
| mcc | 0.860295 | 0.528751 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 214 | 15 |
| Labeled as 1 | 17 | 212 |
| Model | Weight |
|---|---|
| 72_NearestNeighbors | 3 |
| 75_CatBoost | 8 |
| 76_CatBoost | 9 |
| 83_CatBoost | 19 |
| 83_CatBoost_BoostOnErrors | 3 |
| score | threshold | |
|---|---|---|
| logloss | 0.0914001 | nan |
| auc | 0.995748 | nan |
| f1 | 0.965665 | 0.12503 |
| accuracy | 0.965066 | 0.12503 |
| precision | 1 | 0.935736 |
| recall | 1 | 7.52959e-05 |
| mcc | 0.930699 | 0.12503 |
| score | threshold | |
|---|---|---|
| logloss | 0.0914001 | nan |
| auc | 0.995748 | nan |
| f1 | 0.965665 | 0.12503 |
| accuracy | 0.965066 | 0.12503 |
| precision | 0.949367 | 0.12503 |
| recall | 0.982533 | 0.12503 |
| mcc | 0.930699 | 0.12503 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 217 | 12 |
| Labeled as 1 | 4 | 225 |